Document details

Microtheories for SDI - Accounting for diversity of local conceptualisations at a global level

Author(s): Duce, Stephanie Jane

Date: 2009

Persistent ID: http://hdl.handle.net/10362/8252

Origin: Repositório Institucional da UNL

Subject(s): Microtheories SDI; Cartography; Semantic heterogeneity; Spatial Data; Infrastructures


Description

The categorization and conceptualization of geographic features is fundamental to cartography, geographic information retrieval, routing applications, spatial decision support and data sharing in general. However, there is no standard conceptualization of the world. Humans conceptualize features based on numerous factors including cultural background, knowledge, motivation and particularly space and time. Thus, geographic features are prone to multiple, context-dependent conceptualizations reflecting local conditions. This creates semantic heterogeneity and undermines interoperability. Standardization of a shared definition is often employed to overcome semantic heterogeneity. However, this approach loses important local diversity in feature conceptualizations and may result in feature definitions which are too broad or too specific. This work proposes the use of microtheories in Spatial Data Infrastructures, such as INSPIRE, to account for diversity of local conceptualizations while maintaining interoperability at a global level. It introduces a novel method of structuring microtheories based on space and time, represented by administrative boundaries, to reflect variations in feature conceptualization. A bottom-up approach, based on non-standard inference, is used to create an appropriate global-level feature definition from the local definitions. Conceptualizations of rivers, forests and estuaries throughout Europe are used to demonstrate how the approach can improve the INSPIRE data model and ease its adoption by European member states.

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Document Type Master thesis
Language English
Advisor(s) Llavori, Rafael Berlanga; Janowicz, Krzysztof; Kuhn, Werner
Contributor(s) Duce, Stephanie Jane
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